Responsibilities:

• Develop and deploy machine learning models that will have a profound impact on our product(s) and end users
• Analyze large datasets to identify trends and patterns
• Work across a range of use cases to improve the quality of LLM output chains
• Plan and implement MLOps, including benchmark monitoring for quality assurance and compliance
• Provide strategic input for long-term data initiatives, including data governance and ethical AI practices
• Work closely with engineers and stakeholders to implement innovative solutions
• Mentor junior data scientists

Requirements & Skills:

• Relevant tertiary qualification, Doctorate or Master’s in Data Science, Mathematics, Statistics, Computer Science, or related field, AND 4+ years industry working experience
• Strong demonstrated history of data science experience and can concisely share examples of successful past projects
• Ideally, you bring commercial experience with NPL techniques (supervised NLP learning with LSTM/CNN/Transformers and/or topic modelling), and;
• Commercial experience with GPT (langchain, llama index, RAG, multi-agent framework).
• Advanced SQL and 2+ years’ programming experience in Python and Natural Language Processing
• Excellent communicator with stakeholders at all levels
• Empathetic, collaborative, open to feedback
• Able to read and keep abreast of LLM-related research
• Able to thrive in an agile environment
• A Master’s/Doctorate in a relevant discipline is a plus
• Able to attend our beautiful Sydney CBD office 2 days a week

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Responsibilities:

• Write and test product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.

Requirements & Skills:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with state-of-the-art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Master’s degree or PhD in Computer Science or a related technical field.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

The post Senior Software Engineer – AI/ML GenAI, Google appeared first on AI Jobs Latest.

Responsibilities:

• Design, develop, and implement API integrations with Gen AI technologies such as GPT, Gemini, and other relevant platforms to enhance business applications.
• Provide technical expertise in AI concepts, including NLP, Deep learning, and LLMs. Ability to tune/train LLM Models and leverage techniques to optimize outputs for relevance, completeness, and quality.
• Create evaluation frameworks to determine model accuracy.
• Provide regular model accuracy reports.
• Collaborate with product managers, data scientists, and software engineers to develop AI-driven solutions that meet business requirements.
• Optimize the performance of AI models and integrations to ensure efficiency, scalability, and reliability.
• Stay up-to-date with the latest advancements in AI technologies and recommend innovative solutions to improve existing systems.
• Create and maintain comprehensive documentation for AI models, API integrations, and technical processes.
• Identify and resolve technical issues related to AI integrations and model performance.
• Provide training and support to internal teams on the use and implementation of AI technologies.
• Ensure that Personal Information and security policies are respected when working with training data, if any.

Requirements & Skills:

• Education: Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
• Experience: Minimum 2 years of experience in AI development
• Proficiency in programming languages such as Python
• Strong understanding of NLP, LLM concepts, and Gen AI models implementation, deployment, and evaluation.
• Strong understanding of MLOPs concepts such as continuous training, continuous monitoring, and continuous improvements to machine learning and AI systems
• Hands-on experience with Gen AI technologies such as GPT, Gemini, Claude, BERT, etc.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Certifications in AI/ML, cloud platforms, and related areas.
• Experience with meta-learning, few-shot learning, or prompt engineering for LLMs
• Knowledge of RESTful APIs and web services.
• Experience with Agentic AI and designing and building solutions is also preferred
• Have deployed Gen AI systems into production.

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Responsibilities:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs and agent-based workloads at scale.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment.

Requirements & Skills:

• 4+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Deep understanding of concurrency, memory management, networking, and distributed systems.
• Experience with containers, virtualization, and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to have:

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.
• Knowledge of ML frameworks (e.g., PyTorch or TensorFlow) and how to optimize them for production serving.
• Experience with model inference optimizations such as quantization, distillation, speculative decoding, etc.
• Familiarity with emerging agent frameworks such as OpenHands, Agent2Agent, and MCP.

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Responsibilities:

• Develop and implement large-scale model architectures, leveraging model scaling and transfer learning techniques.
• Prioritize training scalability and signal scaling to optimize model performance, efficiency, and reliability.
• Develop and apply NextGen sequence learning techniques to drive advancements in natural language processing and understanding.
• Design and implement generative modeling solutions for data augmentation.
• Research and develop graph-aware large language models.
• Develop and deploy AutoML pipelines.
• Apply Reinforcement Learning (RL) techniques, including long-term value optimization, RLHF, and RL4Reason.
• Use causal learning to identify and understand the cause-and-effect relationships across data.
• Collaborate with cross-functional teams to design and optimize ML systems, leveraging expertise in hardware-software co-design, including quantization, compression, and resource-efficient AI, to drive performance improvements and efficiency gains.
• Develop and implement innovative solutions for data-related challenges, utilizing knowledge of semi/self-supervised learning, generative techniques, sampling, debiasing, domain adaptation, continual learning, data augmentation, cold-start, content understanding, and large language models.

Requirements & Skills:

• Currently has, or is in the process of obtaining, a Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience. The degree must be completed prior to joining Meta
• Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Computer Engineering, Artificial Intelligence, Machine Learning, or a relevant technical field.
• Research experience in deep learning, reinforcement learning, natural language processing, computer vision, recommendations, ranking, search, or related areas.
• Programming experience in Python and hands-on experience with frameworks such as PyTorch.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
• First author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, ACL).
• Experience taking ideas from research to production.
• Experience working and communicating cross-functionally in a team environment.
• Experience solving complex problems and comparing alternative solutions, tradeoffs, and different perspectives to determine a path forward.

The post Research Engineer – Monetization AI, Meta appeared first on AI Jobs Latest.

Responsibilities:

• Write and test product or system development code.
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.

Requirements & Skills:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with state-of-the-art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Master’s degree or PhD in Computer Science or a related technical field.
• 1 year of experience in a technical leadership role.
• Experience developing accessible technologies.

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